Title:

Flash Thermography Imaging for Nondestructive Evaluation of Additively Manufactured Metallic Structures in Nuclear Applications

Speaker:

Dr. Alexander Heifetz

Affiliation:

Principal Electrical Engineer, Nuclear Science and Engineering Division at Argonne National Laboratory

When:

Thursday, January 28, 2021 at 11:00:00 AM   Add to Calendar

Where:

https://bluejeans.com/172812180 Building

Host:

Anna Erickson
dbrown3602gatech.edu

Abstract

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex-shape stainless steel and Inconel structures for nuclear reactors. AM of such metallic structures is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores. Integrity of AM structures needs to be evaluated nondestructively before their deployment in a nuclear reactor. Flash thermography provides a capability for non-contact nondestructive evaluation (NDE) of sub-surface pores in arbitrary size structures, with the possibility of in-service structural health monitoring. Flash thermography measures material response to thermal impulse deposited on material surface with a flash lamp. Measurements data cube consists of images of material transient surface temperature acquired with fast frame infrared camera. Information about material internal structure is contained in surface temperature transients because thermal resistance of internal structures (e.g., pores) affects local surface temperature decay rate. We have investigated several approaches to detection of material defects in flash thermography data, included thermal tomography computational method to obtain depth reconstruction, and unsupervised machine learning to enhance signal to noise ratio of features in thermal images. Performance of different methods was benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced LPBF method with imprinted calibrated porosity defects.

Biography

Dr. Alexander Heifetz (BS Engineering Science, MS Physics, PhD Electrical Engineering, all from Northwestern University) is a Principal Electrical Engineer with the Nuclear Science and Engineering Division at Argonne National Laboratory. He joined Argonne in 2008 as Director’s Postdoctoral Fellow. His current research is on non-destructive evaluation (NDE) of additively manufactured metals and concrete, machine learning for thermal hydraulic sensing, and development of flow sensor for high temperature molten. His work is sponsored by DOE Nuclear Energy Enabling Technology (NEET) Advanced Methods in Manufacturing (AMM) program, NEET Advanced Sensors and Instrumentation (ASI) program, and Advanced Research Projects Agency – Energy (ARPA-E). Dr. Heifetz has published over 70 journal and conference proceedings papers, and has three granted US patents. He shared the Best Paper Award at the 2019 and 2020 IEEE International Conference on Electro/Information Technology. Dr. Heifetz is a member of Northwestern Argonne Institute for Science and Engineering (NAISE), and he is an Adjunct Professor at the Civil, Materials and Environmental Engineering Department at the University of Illinois at Chicago. He also serves as Argonne point of contact for ETI and MTV NNSA university consortia.